In 2015, the Girl Scouts of Western Washington received a donation for $100,000 to help them support poorer scouts with a significant string attached: no support for transgender girls. The Girl Scouts rejected this assault on their values, returned the donation, and launched #forEVERYgirl, an effort to make up the difference in their funding. The campaign raised over $300,000.
Not every story like this has a happy ending. When there is dependance on funding sources, that dependance can be used as leverage.
Right now, there is a debate at the University of Texas at Austin about the playing of the song “The Eyes of Texas” because it has also traditionally been performed at minstrel shows and its title comes from a saying from Robert E. Lee. The band has refused to play the song, so a pre-recorded version has been used at sporting events.
For several donors, the UT-Austin defense of the song has not been sufficiently vocal and thus have begun pulling at the strings attached to their donations:
And it doesn’t have to be just hot-button issues. In 2020, we saw the challenges of being dependent on some things that were taken as givens: ticket sales, galas, 5Ks, canvassing, human contact, etc.
Independence from these pressures or scenarios is something that must be planned, usually including:
A broad-based omnichannel direct marketing program. This makes it so that challenges in one channel could be taken up by others. It also makes it so that major donors who try to pull strings could be replaced by the next donor in the portfolio or an emergency appeal to your loyal smaller donors.
A sufficiently well-known and well-regarded brand that you can take challenges public. The Girl Scouts’ brand was at least partially responsible for their fundraising prowess in overcoming transphobia—when one sees two sides in a fight and the Girl Scouts are one side, one must reconsider picking the other side. Same for other nonprofit brands that have invested in goodwill.
A diverse base of supporters and the investment in creating this base. This is certainly within limits— it’s understandable, for example, that Catholic Charities gets most of their donations from Catholics. But stop me when I get to something that doesn’t ring true:
“Our average donor is in their late 50s-early 60s, with mail donors skewing older and digital donors skewing slightly younger. We also skew whiter, more affluent, and more highly educated than the general public. Our revenues skew even more than way, given that the more affluent give us more on average.”
When your donor base skews older, whiter, and more affluent, you will be able to fundraise most successfully for the concerns of those who are older, whiter, and more affluent.
It takes time and treasure to change this. One of the most successful forms of digital modeling is literally called lookalikes, with the selling feature that it will find donors that look the most likely your present donor base. To create a doesn’t-look-alike model is much more statistically difficult.
But the work must be done. Whether dependent on individual funders or on the systems subject to the past year that looked like someone was playing SimCity drunk (pandemic! mail issues! murder hornets! coin shortage! insurrection! Godzilla!), the missions of our nation’s great causes are too important to be fragile. Thus, we must build for independence.